Hydro-Qu&amp;#x00E9;bec's challenges and experiences in on-line DSA applications

Loud, L.; Guillon, Sébastien; Vanier, G.; Huang, Jinan; Riverin, L.; Lefebvre, Daniel; Rizzi, J.-C.

doi:10.1109/pes.2010.5588120

Cited by 9 publications

(7 citation statements)

References 9 publications

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“…Distributed and parallel processing has become an essential technique in modern online DSA systems [36,[42][43][44][45][46]. This technique can effectively accomplish significant speed improvement as the TSA usually includes the assessment of many contingencies.…”

Section: High Performance Computingmentioning

confidence: 99%

“…In [43], the authors have reported a significant and almost linear reduction of the computation time by using the parallel processing in multi-core processors.…”

Section: High Performance Computingmentioning

confidence: 99%

“…These limits are stored in a database and accessed based on similarity of the on-line operating conditions obtained from the real power system in operations [43]. This is obviously a very fast method to obtain the stability limits as it requires no additional simulations or calculations.…”

Section: Other Approachesmentioning

confidence: 99%

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Application of energy-based power system features for dynamic security assessment

Geeganage

Annakkage

Weekes

et al. 2015

2015 IEEE Power &Amp; Energy Society General Meeting

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To date, the potential of on-line Dynamic Security Assessment (DSA)-to monitor, alert, and enhance system security-is constrained by the longer computational cycle time. Traditional techniques requiring extensive numerical computations makes it challenging to complete the assessment within an acceptable time. Longer computational cycles produce obsolete security assessment results as the system operating point evolves continuously. This thesis presents a DSA algorithm, based on Transient Energy Function (TEF) method and machine learning, to enable frequent computational cycles in on-line DSA of power systems.The use of selected terms of the TEF as pre-processed input features for machine learning demonstrated the ability to successfully train a contingency-independent classifier that is capable of classifying stable and unstable operating points. The network is trained for current system topology and loading conditions. The classifier can be trained using a small dataset when the TEF terms are used as input features. The prediction accuracy of the proposed scheme was tested under the balanced and unbalanced faults with the presence of voltage sensitive and dynamic loads for different operating points. The test results demonstrate the potential of using the proposed technique for power system on-line DSA. Power system devices such as HVDC and FACTS can be included in the algorithm by incorporating the effective terms of a corresponding TEF.An on-line DSA system requires the integration of several functional components.Some of these components already exist and the others are newly introduced to the i power system. The practicality of the proposed technique in terms of a) critical data communications aspects b) computational hardware requirements; and c) capabilities and limitations of the tools in use was tested using an implementation of an on-line DSA system. The test power system model was simulated using a real-time digital simulator. The other functional units were distributed over the Local Area Network (LAN). The implementation indicated that an acceptable computational cycle time can be achieved using the proposed method.In addition, the work carried out during this thesis has produced two tools that can be used for a) web-based automated data generation for power system studies; and b) testing of on-line DSA algorithms.ii

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Section: High Performance Computingmentioning

confidence: 99%

“…In [43], the authors have reported a significant and almost linear reduction of the computation time by using the parallel processing in multi-core processors.…”

Section: High Performance Computingmentioning

confidence: 99%

See 1 more Smart Citation

Application of energy-based power system features for dynamic security assessment

Geeganage

Annakkage

Weekes

et al. 2015

2015 IEEE Power &Amp; Energy Society General Meeting

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“…Using information computed offline to inform online operation has been applied in the past (e.g. [28]) but the iTesla platform implements this idea at an unprecedented scale, paving the way for DSA at the pan-European level. We indicatively mention that analyzing post-fault stability of 5000 operating points across a list of 1000 contingencies (France alone has almost 2000 credible contingencies) requires 5 million dynamic simulations.…”

Section: Introductionmentioning

confidence: 99%

Implementation of a Massively Parallel Dynamic Security Assessment Platform for Large-Scale Grids

Konstantelos

Jamgotchian²,

Tindemans

et al. 2017

IEEE Trans. Smart Grid

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Abstract-This paper presents a computational platform for dynamic security assessment (DSA) of large electricity grids, developed as part of the iTesla project. It leverages High Performance Computing (HPC) to analyze large power systems, with many scenarios and possible contingencies, thus paving the way for pan-European operational stability analysis. The results of the DSA are summarized by decision trees of 11 stability indicators. The platform's workflow and parallel implementation architecture is described in detail, including the way commercial tools are integrated into a plug-in architecture. A case study of the French grid is presented, with over 8000 scenarios and 1980 contingencies. Performance data of the case study (using 10,000 parallel cores) is analyzed, including task timings and data flows. Finally, the generated decision trees are compared with test data to quantify the functional performance of the DSA platform.Index Terms-High performance computing, Monte Carlo methods, power system simulation, power system stability.

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“…Preventive control systems, on the other hand, determine if a remedial action must be taken in response to the next contingency. The design of a preventive control system, which is the scope of this study, mainly relies on accurate stability analysis of contingency scenarios [3]. Traditionally, all possible contingencies are simulated off-line to assess network stability limits, regardless of the prevailing system conditions.…”

Section: Introductionmentioning

confidence: 99%

A PMU-augmented stability power limit assessment for reliable arming of special protection systems

Zamani

Beresh

Cress

2015

Electric Power Systems Research

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Hydro-Québec's challenges and experiences in on-line DSA applications

Cited by 9 publications

References 9 publications

Application of energy-based power system features for dynamic security assessment

Application of energy-based power system features for dynamic security assessment

Implementation of a Massively Parallel Dynamic Security Assessment Platform for Large-Scale Grids

A PMU-augmented stability power limit assessment for reliable arming of special protection systems

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